This work was supported by the National Natural Science Foundation of China (No. 71271015, 70971006, 70831001), and was done while Ping Li was visiting Columbia University and the University of South Carolina. We acknowledge Steven Kou and Zhiliang Ying of Columbia University and Hong Yan of the University of South Carolina for their helpful discussions. We are also very grateful to the anonymous referee, the EFM journal editor John Doukas and the English editor Joelma Nascimento for their great work on improving the quality of the paper.
Change Analysis for the Dependence Structure and Dynamic Pricing of Basket Default Swaps
Article first published online: 1 DEC 2013
© 2013 John Wiley & Sons Ltd
European Financial Management
Volume 21, Issue 4, pages 646–671, September 2015
How to Cite
Li, P. and Li, Z.-Z. (2015), Change Analysis for the Dependence Structure and Dynamic Pricing of Basket Default Swaps. European Financial Management, 21: 646–671. doi: 10.1111/eufm.12036
- Issue published online: 21 SEP 2015
- Article first published online: 1 DEC 2013
- National Natural Science Foundation of China. Grant Numbers: 71271015, 70971006, 70831001
- change analysis;
- basket default swap;
- dynamic copula;
- dependence structure
In this paper we use a type of dynamic copula method to characterise the dependence structure between financial assets and price basket default swaps (BDSs). We first employ a goodness-of-fit test and a binary segmentation procedure to analyse the change of dependence structure between the obligations underlying a BDS, then present a numerical example to demonstrate the change analysis and BDS pricing process. We find that in different time periods, the best copula fitting the data is not the same; therefore the tranche spreads of the BDS are also different. We also compare our results with those obtained from static copulas and dynamic Gaussian copulas. The results show that the static copula and dynamic Gaussian copula methods underestimate the spreads for riskier tranches and overestimate those for less risky tranches.